Climate Change and AI: Understanding Economic Impact – Michael Ferrari, Climate Alpha

This is Techron tv. Hello everyone. Welcome to techron tv.

I'm Bonnie Schneider. Today we're talking about climate change, its financial impact, and how AI is providing solutions. I'm pleased now to welcome Dr.

Michael Ferrari, chief Scientific and commercial Officer at Climate Alpha to Techstrong tv. Dr. Ferrari's deep tech and commercial interface experience gives him a unique perspective on the challenges of climate change and its repercussions in the global economy.

Dr. Ferrari, it's a pleasure to have you on Techstrong tv. Thanks, Bonnie.

Great to be here. Great. Well, can you share with us a little bit more about your background and the mission of Climate Alpha?

Uh, sure. I'll start with Climate Alpha, uh, and then I'll talk a little bit about my background and how it all comes together. So, um, what Climate Alpha really is focused on is, you know, the spectrum of climate driven opportunity.

So when we think about what's happening with climate change and climate volatility, a lot of people, particularly in the financial, uh, sector, go directly towards the risk side of the equation. And what we look to do is really, uh, it's still part of the same continuum, but we really try to focus on where to deploy capital to better protect ourselves, to better understand where some of the climate driven opportunities are, adopt investors and asset managers, uh, along the ride for this journey. So, um, a lot of climate information, which, uh, you very well know.

Uh, it's very esoteric. Sometimes it's very difficult to translate and understand for people that don't work with the data every day. So we really work with partners, just try to understand what data's important, what's meaningful, and ultimately where to spot opportunities for the decades ahead.

Can you tell, and in my particular, oh, go ahead. I'm sorry. Go ahead.

I was just saying, just my background in terms of how I got into this space. I mean, I've kind of been in the climate finance, uh, data science space for, you know, 25 years or so. Um, but I started off as a commodities trader.

So, uh, my first role at a graduate school was actually trading physical commodities, you know, things like agriculture and energy materials, all that have kind of a climate fingerprint. Uh, and then I kind of never looked back from there. So I kind of didn't take the traditional academic route and went right to the commercial sector, but still started to work with climate data and climate models and put that into a, you know, kind of how a financial, uh, risk manager may wanna use that data.

That is a smart move. I, I, my background is as a meteorologist, so, um, I can appreciate that you, you chose that. That's great.

Um, well, I was wondering if you could detail the process of using AI to build complex models that factor into climate risks and macroeconomic trends and demographic shifts. Sure. And, uh, I mean, there's, it's a fascinating area because, uh, as, uh, any emerging technology right now, AI is kind of the, the buzzword and, you know, every new technology, every new deployment seems to have an AI layer embedded within it.

And, you know, what we try to do is really use it for, you know, for two things. One is to obviously sift through the massive amounts of data, not just climate data, but climate data in the context of a variety of other types of data, and understand what data is important and what data is maybe less important. So a lot of this comes down to when we get into data science speak, what's around feature selection?

So we have climate data that's coupled with your point macroeconomic data, social data, demographic data, um, you know, a variety of data that is not necessarily climate specific. And we use data to AI to try to understand what those relationships are. And then if we are going to build a model on top of that, you know, what are the features that are important to a model versus what things may be overfit or just redundant in terms of data.

So, um, we have a lot of data now. When I, I think when I started my career, the issue was just not having enough data to tell a coherent story. Now we're at the other end of the spectrum where we have more data than we know what to do, and it's really trying to find out where those important slices of data may lie.

Hmm, that makes sense. Um, how do carbon emissions and their interaction with other variables create market volatility? Um, when it comes to carbon emissions, I would tend to maybe widen the aperture a little bit.

There is a lot of focus specifically on, uh, on particularly, and we talk about E S G, right? Environmental, social and governance, which is kind of driving a lot of financial decision making. Now, a lot of the e piece, uh, it focuses specifically on carbon.

And within carbon it even focuses, focuses specifically on what are called scope three emissions. So, you know, most companies have, you know, scope one, two, and three emissions that they can kind of categorize. Uh, scope three is actually the largest component of that emission, uh, base.

It's also the most uncertain and, uh, probably the least well documented. So instead of focusing just on that emission spectra, uh, we may look at emissions as part of a broader category of environmental data. And I think what we're seeing now is, uh, again, those of those that have been in the space, I've known it for a while, but we're seeing a lot of impacts, both positive and and negative on how climate driven volatility does impact performance.

Um, a lot of times it was usually the things that come to mind are kind of the extreme events, you know, when think about hurricanes and floods and droughts. Uh, but what we have now with more data that's become available is there are a lot more climate related risks that are, you know, somewhat more insidious. Sometimes they just take a long time to materialize.

And then you kind of have these, uh, these phase changes where the impacts may be dramatic. Um, what we're looking to do now is understand what is the relationship between these particular variables and the financial outcomes. But we tend to not focus specifically on the emissions piece because we, you know, we think it's just one piece of a puzzle that is much broader.

And when we think about environmental data, you know, this includes water data, includes materiality data, it includes a whole host of data that doesn't necessarily fall under that emissions category. So we try to just take a, a, a wider view when it comes to the environmental piece. That makes sense.

Um, can you discuss how global investors can leverage spatial finance to construct climate proof portfolios that outperform the market? I guess that's the goal for, for many. Yeah, it is.

And, uh, it's an interesting question. I think, I mean, as the name implies, spatial finance is really putting, you know, kind of a, a spatial or a complexity theory type of approach towards financial decisions. So I'll have to default to my background with commodities.

I mean, commod, it's always interesting to know, you know, where stocks and flows are originating from, where they're moving to, how things are being processed and used, how climate influences all that. Uh, but at the end of the day, everything still has a geographic footprint. So it's not just enough to have, you know, the data on the flows.

It has, you know, it's, it's equally important to understand where material is coming from, what balances are, like, how quotas are going to impact what's going into a country, not of another country, um, and understand what those relationships are. So it's really kind of putting together, looking at the global economic engine as kind of a puzzle as opposed to these individual data streams that in that act independently. So it's, um, I always kind of tell people that are interested in this space, whatever your domain is, you almost have to be a student of everything, right?

So, uh, you might be somebody that's really specializes in, you know, a very particular component of the supply chain, but understanding how that fits into pieces around it, how it impacts, you know, buy and spend patterns of companies and processors and producers, um, how foreign an exchange rates impact things. And it really is, you know, every day there's something new happening that we weren't thinking about the day before. So the only way to really look at that is really kind of through this spatial finance lens.

Uh, and I think it is starting to gain some traction. I think it's always been there. I think it's always been more of a niche approach.

Um, but within the last couple years, we're starting to see a lot of, um, larger asset managers and financial institutions really kind of abrasive approach and realize that there is, uh, a different way of looking data. And this, uh, you know, those of us that have been in this space have, have always felt it was important. It's finally starting to gain some recognition.

Um, can you describe what the resilience index is for those that are unfamiliar with it and other composite data sets and, and how, um, that the adaptation is imperative in North America and globally? I, I was just reading about new requirements from the eu, um, regarding reporting. So I was just wondering if you could kind of break that down for everyone.

Sure. Uh, very timely too. So, uh, and this goes back to how we kind of started the conversation.

You know, instead of just focusing on the risk side, when we look at the resilience side, you know, we're looking at how, you know, companies, economies, locations are going to, you know, not only sustain potential shocks, but also benefit from 'em. So we're looking at not just where capital might be going, but why capital might be directed in certain areas. So if we think about the, uh, you know, the changing energy infrastructure, just as an example, it's not just about switching from the internal combustion engine to battery electric vehicles.

It's understanding what areas are going to be well positioned to build a charging infrastructure around it. Um, what areas are gonna have the, the right mix of, uh, of traditional and renewable energy to support that transition. Uh, what areas actually have a favorable tax base that's gonna incentivize workers to move these locations?

So it goes from just understanding, you know, where it should not be deploying capital to where it should, but also, you know, answering the why piece, why these are important factors to be thinking about as an investor. Um, now when we think about the, the North American piece that you referenced, and it really does kind of, it, it goes well beyond North America, I think from a regulatory perspective, we've always kind of been following what's happening in the eu. EU tends to mandate things and put them in practice a little bit earlier.

And the US based, uh, mandates and series of regulations, they tended to work more on a trial basis, and then, you know, over time they might be three or four years behind the EU and then start to implement it. We're seeing that similar now, um, when it comes to financial disclosures around climate. So, um, you know, in the past, companies were required to show what their financial risk was, uh, but it wasn't really very well defined.

And I think when you look at the, the current regulations that are coming out through the S E c, uh, it's not only banked, it's gonna be any companies that are managing assets. They're, they're gonna have to disclose this information now, how, how good the data is that goes into that disclosure and, and what it actually means. That still is up for discussion, but at least we're moving from kind of waiting and seeing and just kind of trialing towards moving towards a, a framework that a lot of this information is gonna be required and it's gonna be mandated like any other piece of financial disclosure information.

Well, our viewers are very, um, interested in it in general and DevOps specifically. And I was wondering if you could speak to the surge in the adaptation of adoption, rather of AI machine learning technologies. In your view, how can these technologies best be used to tackle the challenges of climate change?

Uh, that's, uh, well, I mean, we could probably spend, uh, hours talking about that one. Uh, but a few that certainly come to mind, you know, one is understanding the, the spectrum of technology is gonna be required to support the energy transition. So I'm gonna keep going back to that because it is such a topical area right now.

Um, there's no panacea for moving from decarbonize, you know, decarbonizing operations towards something that is, uh, that is less polluting. Um, and moving from kind of this, you know, what we call the ICE to bev transition in vehicles, one of the things that I can actually do now is allow us to understand that broad spectrum of possibilities, uh, in a way that we just weren't able to do before. Um, we're able to do it with it.

It's less about precision. So a lot of times, uh, users, uh, particularly the DevOps side, think that we're gonna be able to develop a better set of answers. And what I'm finding, uh, and I think others in the field are starting to confirm this, it's less about finding those specific answers.

It's providing answers maybe with different data and more conviction. So as a user, right, or as somebody that might be implementing the output, they may come up with the same conclusion, but they may do it with a different set of data that supports that conclusion, which adds to conviction. If you're thinking about, you know, implementing any sort of capital allocation discussion, you know, obviously you want reasons, you want data to back up those reasons why you might be, you know, undertaking a certain position.

And, uh, so what we can do, and, and I think this is where kind of, of the, the DevOps piece is, is super important. We're, we're even starting to see this internally is, you know, one potential outcome is we're going to, you know, find new answers, which is great. But the second one really is understanding those important answers with more conviction and doing it with data that's differentiated.

And again, going back to the spatial piece, really understanding the relationships between the data, um, in ways that we just have not been able to do in the past. How do you see your company supporting, uh, DevOps? You know, a lot of people that are watching us on techstrong tv, they're looking for solutions, uh, to make their jobs, um, easier, more efficient, and, and, and in this case, more sustainable.

So how do you see Climb Alpha supporting it and DevOps From the perspective of DevOps, uh, as practitioners? Yes. Um, and an easy way is, uh, uh, around energy management, right?

I mean, that's usually the first thing that comes to mind if, uh, I mean, AI comes with some baggage too, right? So just because we're deploying models, uh, we're also spending a lot more compute cycles now. We're also spending a lot more energy just to construct these models.

So the models are great, and the amount of data we have is great, but it comes at a cost. So I think one way that we can, uh, you know, kind of help steer the discussion in a positive direction is really to optimize that DevOps stage and get a better handle on what our spend is, what compute cycles are important, and, you know, run our own operations a little bit more efficiently, which extend beyond the individual companies. And this really gets into cloud management at large, right?

How can large scale, um, you know, compute cycles be managed in a way that they haven't been able to do before? And, uh, there's a lot of issues around energy, around water, you know, all these things that are related to running an operation and, uh, they haven't been very well understood until somewhat recently. So I think this is one area we can certainly help, um, you know, provide some benefit.

Finally, if you can share with me, what are the future goals of Climate Alpha in, um, assisting people and, and companies adapting to climate volatility? Sure. Um, well there, there's a couple different areas.

One, uh, starting with financial institutions and asset managers, it's, you know, as we've been discussing, how can we spot opportunities that are going to hopefully appreciate as, again, climate in conjunction with these other trends, uh, start to materialize. And what we're kinda looking at is climate to become a tailwind. Um, a lot of the previous, uh, information that has been probably discussed in this space over the last 10, 20 years, it really, uh, it, it was kind of a mismatch of data and expectations.

Uh, so climate, the, the climate piece, the climate premium, if you will, has not necessarily been priced in. We think that's going to become more apparent going forward. So we're looking to help, uh, asset managers better position where that climate premium should lie, uh, and how to position a portfolio around that.

So, uh, at the asset manager level, that's one area. Uh, but the second is even done to individuals. I mean, if you're looking to buy a home, if you're looking to purchase property somewhere, if you're looking to relocate, you know, really what is the climate risk or the opportunity in terms of a, what you're trying to sell and b, where you're looking to buy.

Um, that hasn't been very well understood, and I think we're bringing some clarity to that discussion. Uh, and hopefully to become just like your, if you're gonna purchase a new property and you look at, you know, school rent, everything else you wanna look at, what is your, you know, your, your climate delta, your climate risk, or your climate resilience piece, and understand how that may, uh, play itself out over the course of your investment lifetime. So, um, it can span everywhere from large financial institutions all the way down to an individual home buyer.

Great, uh, example of the, the size and scope of the services that Climate Alpha can provide. Thank you, Dr. Michael Ferrari, chief Scientific and Commer Chief Commercial Officer at Climate Alpha.

We really appreciate you joining us on Techstrong TV today. Thank you. Thanks All.

Well stay with us. We'll have more on Techstrong TV coming up.